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include developing foundation models for genome interpretation; creating methods for multi-omic and spatial data analysis and integration with phenotypic and clinical data; and advancing AI-based frameworks
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of environmental seismology, an emerging field focused on interpreting seismic signals generated by surface processes. This interdisciplinary PhD project aims to integrate hydraulic measurements, physical models and
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. The research in the PhD project will focus on core spatio-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation
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Building engineer or Environmental Science, Planning, Engineering, computer science, innovation science or related fields with demonstrable experience in spatial analysis and numerical modelling
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references.. The Michigan Neuroscience Institute is an inclusive workplace that encourages individuals from diverse backgrounds and with diverse experiences to apply. Please visit: https://medicine.umich.edu
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will allow exploration of various forest configurations, including differences in tree density, species, and spatial distribution. Laboratory experiments will complement these models, using scaled-down
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networks, and how these can be exploited for therapeutic intervention. We employ state-of-the-art in vitro and in vivo models to dissect cancer biology and develop new strategies to target key
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bright points to solar jets, called spicules. The study will involve mathematical modelling complemented with observational data analysis using high spatial, temporal and spectral resolution solar
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dynamics that incorporates the effects of pesticides (from the above experiments) as well as spatial processes such as dispersal and species interactions.4. Bridge data and theory – Test model predictions
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. This involves the development of mathematical models for signal transmission/reception, derivation of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or